def get_metadata_czi(filename, dim2none=False, convert_scunit=True):
"""
Returns a dictionary with CZI metadata.
Information CZI Dimension Characters:
- '0':'Sample', # e.g. RGBA
- 'X':'Width',
- 'Y':'Height',
- 'C':'Channel',
- 'Z':'Slice', # depth
- 'T':'Time',
- 'R':'Rotation',
- 'S':'Scene', # contiguous regions of interest in a mosaic image
- 'I':'Illumination', # direction
- 'B':'Block', # acquisition
- 'M':'Mosaic', # index of tile for compositing a scene
- 'H':'Phase', # e.g. Airy detector fibers
- 'V':'View', # e.g. for SPIM
:param filename: filename of the CZI image
:type filename: str
:param dim2none: option to set non-existing dimension to None, defaults to False
:type dim2none: bool, optional
:param convert_scunit: convert scale unit string from 'µm' to 'micron', defaults to False
:type convert_scunit: bool, optional
:return: metadata, metadata_add - dictionaries with the relevant CZI metainformation
:rtype: dict
"""
# get metadata dictionary using pylibCZIrw
czidoc = pyczi.open_czi(filename)
metadatadict_czi = xmltodict.parse(czidoc.raw_metadata)
# get czi object aicspylibczi
aicsczi = CziFile(filename)
# initialize metadata dictionary
metadata = create_metadata_dict()
# get directory and filename etc.
metadata['Directory'] = os.path.dirname(filename)
metadata['Filename'] = os.path.basename(filename)
metadata['Extension'] = 'czi'
metadata['ImageType'] = 'czi'
# get additional data by using aicspylibczi directly
metadata['aicsczi_dims'] = aicsczi.dims
metadata['aicsczi_dims_shape'] = aicsczi.get_dims_shape()
metadata['aicsczi_size'] = aicsczi.size
metadata['isMosaic'] = aicsczi.is_mosaic()
print('CZI is Mosaic :', metadata['isMosaic'])
# get the dimensions of the bounding boxes for the scenes
# metadata['BBoxes_Scenes'] = getbboxes_allscenes(czi, metadata, numscenes=metadata['SizeS'])
metadata['bbox_all_scenes'] = aicsczi.get_all_scene_bounding_boxes()
if aicsczi.is_mosaic():
metadata[
'bbox_all_mosaic_scenes'] = aicsczi.get_all_mosaic_scene_bounding_boxes(
)
metadata[
'bbox_all_mosaic_tiles'] = aicsczi.get_all_mosaic_tile_bounding_boxes(
)
metadata['bbox_all_tiles'] = aicsczi.get_all_tile_bounding_boxes()
# get additional data by using pylibczirw directly
metadata['pyczi_dims'] = czidoc.total_bounding_box
metadata['pyczi_bbox_scenes'] = czidoc.scenes_bounding_rectangle
metadata['pyczi_total_rect'] = czidoc.total_bounding_rectangle
# check which dimension exist inside this CZI file
metadata = checkdims_czi(czidoc, metadata)
# determine pixel type for CZI array
metadata['NumPy.dtype'] = {}
for ch, px in czidoc.pixel_types.items():
metadata['NumPy.dtype'][ch] = get_dtype_fromstring(px)
if czidoc._is_rgb(czidoc.get_channel_pixel_type(0)):
metadata['isRGB'] = True
#if 'A' in aicsczi.dims:
# metadata['isRGB'] = True
print('CZI is RGB :', metadata['isRGB'])
# determine pixel type for CZI array by reading XML metadata
try:
metadata['PixelType'] = metadatadict_czi['ImageDocument']['Metadata'][
'Information']['Image']['PixelType']
except KeyError as e:
print('No PixelType :', e)
metadata['PixelType'] = None
try:
metadata['SizeX'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeX'])
except KeyError as e:
print('No X Dimension :', e)
metadata['SizeX'] = None
try:
metadata['SizeY'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeY'])
except KeyError as e:
print('No Y Dimension :', e)
metadata['SizeY'] = None
try:
metadata['SizeZ'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeZ'])
except KeyError as e:
print('No Z Dimension :', e)
if dim2none:
metadata['SizeZ'] = None
if not dim2none:
metadata['SizeZ'] = 1
try:
metadata['SizeC'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeC'])
except KeyError as e:
print('No C Dimension :', e)
if dim2none:
metadata['SizeC'] = None
if not dim2none:
metadata['SizeC'] = 1
# get dimension of consitent 5D stack using AICSImageio
#aics_img = AICSImage(filename)
#metadata['czi_dims5D_aics'] = aics_img.dims.order
#metadata['czi_shape5D_aics'] = aics_img.dims.shape
#metadata['czi_dict5D_aics'] = aics_img.dims.__dict__
# create empty lists for channel related information
channels = []
channels_names = []
channels_colors = []
# in case of only one channel
if metadata['SizeC'] == 1:
# get name for dye
try:
channels.append(
metadatadict_czi['ImageDocument']['Metadata']['DisplaySetting']
['Channels']['Channel']['ShortName'])
except KeyError as e:
print('Channel shortname not found :', e)
try:
channels.append(
metadatadict_czi['ImageDocument']['Metadata']
['DisplaySetting']['Channels']['Channel']['DyeName'])
except KeyError as e:
print('Channel dye not found :', e)
channels.append('Dye-CH1')
# get channel name
try:
channels_names.append(
metadatadict_czi['ImageDocument']['Metadata']['DisplaySetting']
['Channels']['Channel']['Name'])
except KeyError as e:
try:
channels_names.append(
metadatadict_czi['ImageDocument']['Metadata']
['DisplaySetting']['Channels']['Channel']['@Name'])
except KeyError as e:
print('Channel name found :', e)
channels_names.append('CH1')
# get channel color
try:
channels_colors.append(
metadatadict_czi['ImageDocument']['Metadata']['DisplaySetting']
['Channels']['Channel']['Color'])
except KeyError as e:
print('Channel color not found :', e)
channels_colors.append('#80808000')
# in case of two or more channels
if metadata['SizeC'] > 1:
# loop over all channels
for ch in range(metadata['SizeC']):
# get name for dyes
try:
channels.append(
metadatadict_czi['ImageDocument']['Metadata']
['DisplaySetting']['Channels']['Channel'][ch]['ShortName'])
except KeyError as e:
print('Channel shortname not found :', e)
try:
channels.append(metadatadict_czi['ImageDocument']
['Metadata']['DisplaySetting']['Channels']
['Channel'][ch]['DyeName'])
except KeyError as e:
print('Channel dye not found :', e)
channels.append('Dye-CH' + str(ch))
# get channel names
try:
channels_names.append(
metadatadict_czi['ImageDocument']['Metadata']
['DisplaySetting']['Channels']['Channel'][ch]['Name'])
except KeyError as e:
try:
channels_names.append(
metadatadict_czi['ImageDocument']['Metadata']
['DisplaySetting']['Channels']['Channel'][ch]['@Name'])
except KeyError as e:
print('Channel name not found :', e)
channels_names.append('CH' + str(ch))
# get channel colors
try:
channels_colors.append(
metadatadict_czi['ImageDocument']['Metadata']
['DisplaySetting']['Channels']['Channel'][ch]['Color'])
except KeyError as e:
print('Channel color not found :', e)
# use grayscale instead
channels_colors.append('80808000')
# write channels information (as lists) into metadata dictionary
metadata['Channels'] = channels
metadata['ChannelNames'] = channels_names
metadata['ChannelColors'] = channels_colors
try:
metadata['SizeT'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeT'])
except KeyError as e:
print('No T Dimension :', e)
if dim2none:
metadata['SizeT'] = None
if not dim2none:
metadata['SizeT'] = 1
try:
metadata['SizeM'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeM'])
except KeyError as e:
print('No M Dimension :', e)
if dim2none:
metadata['SizeM'] = None
if not dim2none:
metadata['SizeM'] = 1
try:
metadata['SizeB'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeB'])
except KeyError as e:
print('No B Dimension :', e)
if dim2none:
metadata['SizeB'] = None
if not dim2none:
metadata['SizeB'] = 1
try:
metadata['SizeS'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeS'])
except KeyError as e:
print('No S Dimension :', e)
if dim2none:
metadata['SizeS'] = None
if not dim2none:
metadata['SizeS'] = 1
try:
metadata['SizeH'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeH'])
except KeyError as e:
print('No H Dimension :', e)
if dim2none:
metadata['SizeH'] = None
if not dim2none:
metadata['SizeH'] = 1
try:
metadata['SizeI'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeI'])
except KeyError as e:
print('No I Dimension :', e)
if dim2none:
metadata['SizeI'] = None
if not dim2none:
metadata['SizeI'] = 1
try:
metadata['SizeV'] = np.int(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Image']['SizeV'])
except KeyError as e:
print('No V Dimension :', e)
if dim2none:
metadata['SizeV'] = None
if not dim2none:
metadata['SizeV'] = 1
# get the XY scaling information
try:
metadata['XScale'] = float(
metadatadict_czi['ImageDocument']['Metadata']['Scaling']['Items']
['Distance'][0]['Value']) * 1000000
metadata['YScale'] = float(
metadatadict_czi['ImageDocument']['Metadata']['Scaling']['Items']
['Distance'][1]['Value']) * 1000000
metadata['XScale'] = np.round(metadata['XScale'], 3)
metadata['YScale'] = np.round(metadata['YScale'], 3)
try:
metadata['XScaleUnit'] = metadatadict_czi['ImageDocument'][
'Metadata']['Scaling']['Items']['Distance'][0][
'DefaultUnitFormat']
metadata['YScaleUnit'] = metadatadict_czi['ImageDocument'][
'Metadata']['Scaling']['Items']['Distance'][1][
'DefaultUnitFormat']
except (KeyError, TypeError) as e:
print('Error extracting XY ScaleUnit :', e)
metadata['XScaleUnit'] = None
metadata['YScaleUnit'] = None
except (KeyError, TypeError) as e:
print('Error extracting XY Scale :', e)
# get the Z scaling information
try:
metadata['ZScale'] = float(
metadatadict_czi['ImageDocument']['Metadata']['Scaling']['Items']
['Distance'][2]['Value']) * 1000000
metadata['ZScale'] = np.round(metadata['ZScale'], 3)
# additional check for faulty z-scaling
if metadata['ZScale'] == 0.0:
metadata['ZScale'] = 1.0
try:
metadata['ZScaleUnit'] = metadatadict_czi['ImageDocument'][
'Metadata']['Scaling']['Items']['Distance'][2][
'DefaultUnitFormat']
except (IndexError, KeyError, TypeError) as e:
print('Error extracting Z ScaleUnit :', e)
metadata['ZScaleUnit'] = metadata['XScaleUnit']
except (IndexError, KeyError, TypeError) as e:
print('Error extracting Z Scale :', e)
if dim2none:
metadata['ZScale'] = None
metadata['ZScaleUnit'] = None
if not dim2none:
# set to isotropic scaling if it was single plane only
metadata['ZScale'] = metadata['XScale']
metadata['ZScaleUnit'] = metadata['XScaleUnit']
# convert scale unit to avoid encoding problems
if convert_scunit:
if metadata['XScaleUnit'] == 'µm':
metadata['XScaleUnit'] = 'micron'
if metadata['YScaleUnit'] == 'µm':
metadata['YScaleUnit'] = 'micron'
if metadata['ZScaleUnit'] == 'µm':
metadata['ZScaleUnit'] = 'micron'
# try to get software version
try:
metadata['SW-Name'] = metadatadict_czi['ImageDocument']['Metadata'][
'Information']['Application']['Name']
metadata['SW-Version'] = metadatadict_czi['ImageDocument']['Metadata'][
'Information']['Application']['Version']
except KeyError as e:
print('Key not found:', e)
metadata['SW-Name'] = None
metadata['SW-Version'] = None
try:
metadata['AcqDate'] = metadatadict_czi['ImageDocument']['Metadata'][
'Information']['Image']['AcquisitionDateAndTime']
except KeyError as e:
print('Key not found:', e)
metadata['AcqDate'] = None
# check if Instrument metadata actually exist
if pydash.objects.has(
metadatadict_czi,
['ImageDocument', 'Metadata', 'Information', 'Instrument']):
if metadatadict_czi['ImageDocument']['Metadata']['Information'][
'Instrument'] is not None:
# get objective data
if isinstance(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Objectives']['Objective'],
list):
num_obj = len(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Objectives']['Objective'])
else:
num_obj = 1
# if there is only one objective found
if num_obj == 1:
try:
metadata['ObjName'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Objectives']
['Objective']['Name'])
except (KeyError, TypeError) as e:
print('No Objective Name :', e)
metadata['ObjName'].append(None)
try:
metadata['ObjImmersion'] = \
metadatadict_czi['ImageDocument']['Metadata']['Information']['Instrument']['Objectives'][
'Objective']['Immersion']
except (KeyError, TypeError) as e:
print('No Objective Immersion :', e)
metadata['ObjImmersion'] = None
try:
metadata['ObjNA'] = np.float(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Objectives']
['Objective']['LensNA'])
except (KeyError, TypeError) as e:
print('No Objective NA :', e)
metadata['ObjNA'] = None
try:
metadata['ObjID'] = \
metadatadict_czi['ImageDocument']['Metadata']['Information']['Instrument']['Objectives'][
'Objective']['Id']
except (KeyError, TypeError) as e:
print('No Objective ID :', e)
metadata['ObjID'] = None
try:
metadata['TubelensMag'] = np.float(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['TubeLenses']['TubeLens']
['Magnification'])
except (KeyError, TypeError) as e:
print('No Tubelens Mag. :', e,
'Using Default Value = 1.0.')
metadata['TubelensMag'] = 1.0
try:
metadata['ObjNominalMag'] = np.float(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Objectives']
['Objective']['NominalMagnification'])
except (KeyError, TypeError) as e:
print('No Nominal Mag.:', e, 'Using Default Value = 1.0.')
metadata['ObjNominalMag'] = 1.0
try:
if metadata['TubelensMag'] is not None:
metadata['ObjMag'] = metadata[
'ObjNominalMag'] * metadata['TubelensMag']
if metadata['TubelensMag'] is None:
print(
'Using Tublens Mag = 1.0 for calculating Objective Magnification.'
)
metadata['ObjMag'] = metadata['ObjNominalMag'] * 1.0
except (KeyError, TypeError) as e:
print('No Objective Magnification :', e)
metadata['ObjMag'] = None
if num_obj > 1:
for o in range(num_obj):
try:
metadata['ObjName'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Objectives']
['Objective'][o]['Name'])
except KeyError as e:
print('No Objective Name :', e)
metadata['ObjName'].append(None)
try:
metadata['ObjImmersion'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Objectives']
['Objective'][o]['Immersion'])
except KeyError as e:
print('No Objective Immersion :', e)
metadata['ObjImmersion'].append(None)
try:
metadata['ObjNA'].append(
np.float(metadatadict_czi['ImageDocument']
['Metadata']['Information']['Instrument']
['Objectives']['Objective'][o]['LensNA']))
except KeyError as e:
print('No Objective NA :', e)
metadata['ObjNA'].append(None)
try:
metadata['ObjID'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Objectives']
['Objective'][o]['Id'])
except KeyError as e:
print('No Objective ID :', e)
metadata['ObjID'].append(None)
try:
metadata['TubelensMag'].append(
np.float(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['TubeLenses']
['TubeLens'][o]['Magnification']))
except KeyError as e:
print('No Tubelens Mag. :', e,
'Using Default Value = 1.0.')
metadata['TubelensMag'].append(1.0)
try:
metadata['ObjNominalMag'].append(
np.float(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Objectives']
['Objective'][o]['NominalMagnification']))
except KeyError as e:
print('No Nominal Mag. :', e,
'Using Default Value = 1.0.')
metadata['ObjNominalMag'].append(1.0)
try:
if metadata['TubelensMag'] is not None:
metadata['ObjMag'].append(
metadata['ObjNominalMag'][o] *
metadata['TubelensMag'][o])
if metadata['TubelensMag'] is None:
print(
'Using Tublens Mag = 1.0 for calculating Objective Magnification.'
)
metadata['ObjMag'].append(
metadata['ObjNominalMag'][o] * 1.0)
except KeyError as e:
print('No Objective Magnification :', e)
metadata['ObjMag'].append(None)
# get detector information
# check if there are any detector entries inside the dictionary
if pydash.objects.has(metadatadict_czi, [
'ImageDocument', 'Metadata', 'Information', 'Instrument',
'Detectors'
]):
if isinstance(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Instrument']['Detectors']['Detector'], list):
num_detectors = len(
metadatadict_czi['ImageDocument']['Metadata']['Information']
['Instrument']['Detectors']['Detector'])
else:
num_detectors = 1
# if there is only one detector found
if num_detectors == 1:
# check for detector ID
try:
metadata['DetectorID'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Detectors']['Detector']
['Id'])
except KeyError as e:
print('DetectorID not found :', e)
metadata['DetectorID'].append(None)
# check for detector Name
try:
metadata['DetectorName'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Detectors']['Detector']
['Name'])
except KeyError as e:
print('DetectorName not found :', e)
metadata['DetectorName'].append(None)
# check for detector model
try:
metadata['DetectorModel'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Detectors']['Detector']
['Manufacturer']['Model'])
except KeyError as e:
print('DetectorModel not found :', e)
metadata['DetectorModel'].append(None)
# check for detector type
try:
metadata['DetectorType'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Detectors']['Detector']
['Type'])
except KeyError as e:
print('DetectorType not found :', e)
metadata['DetectorType'].append(None)
if num_detectors > 1:
for d in range(num_detectors):
# check for detector ID
try:
metadata['DetectorID'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Detectors']['Detector']
[d]['Id'])
except KeyError as e:
print('DetectorID not found :', e)
metadata['DetectorID'].append(None)
# check for detector Name
try:
metadata['DetectorName'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Detectors']['Detector']
[d]['Name'])
except KeyError as e:
print('DetectorName not found :', e)
metadata['DetectorName'].append(None)
# check for detector model
try:
metadata['DetectorModel'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Detectors']['Detector']
[d]['Manufacturer']['Model'])
except KeyError as e:
print('DetectorModel not found :', e)
metadata['DetectorModel'].append(None)
# check for detector type
try:
metadata['DetectorType'].append(
metadatadict_czi['ImageDocument']['Metadata']
['Information']['Instrument']['Detectors']['Detector']
[d]['Type'])
except KeyError as e:
print('DetectorType not found :', e)
metadata['DetectorType'].append(None)
# check for well information
metadata['Well_ArrayNames'] = []
metadata['Well_Indices'] = []
metadata['Well_PositionNames'] = []
metadata['Well_ColId'] = []
metadata['Well_RowId'] = []
metadata['WellCounter'] = None
metadata['SceneStageCenterX'] = []
metadata['SceneStageCenterY'] = []
try:
print('Trying to extract Scene and Well information if existing ...')
# extract well information from the dictionary
allscenes = metadatadict_czi['ImageDocument']['Metadata'][
'Information']['Image']['Dimensions']['S']['Scenes']['Scene']
# loop over all detected scenes
for s in range(metadata['SizeS']):
if metadata['SizeS'] == 1:
well = allscenes
try:
metadata['Well_ArrayNames'].append(allscenes['ArrayName'])
except KeyError as e:
try:
metadata['Well_ArrayNames'].append(well['Name'])
except KeyError as e:
# print('Well Name not found :', e)
try:
metadata['Well_ArrayNames'].append(well['@Name'])
except KeyError as e:
# print('Well @Name not found :', e)
print('Well Name not found :', e,
'Using A1 instead')
metadata['Well_ArrayNames'].append('A1')
try:
metadata['Well_Indices'].append(allscenes['Index'])
except KeyError as e:
try:
metadata['Well_Indices'].append(allscenes['@Index'])
except KeyError as e:
print('Well Index not found :', e)
metadata['Well_Indices'].append(1)
try:
metadata['Well_PositionNames'].append(allscenes['Name'])
except KeyError as e:
try:
metadata['Well_PositionNames'].append(
allscenes['@Name'])
except KeyError as e:
print('Well Position Names not found :', e)
metadata['Well_PositionNames'].append('P1')
try:
metadata['Well_ColId'].append(
np.int(allscenes['Shape']['ColumnIndex']))
except KeyError as e:
print('Well ColumnIDs not found :', e)
metadata['Well_ColId'].append(0)
try:
metadata['Well_RowId'].append(
np.int(allscenes['Shape']['RowIndex']))
except KeyError as e:
print('Well RowIDs not found :', e)
metadata['Well_RowId'].append(0)
try:
# count the content of the list, e.g. how many time a certain well was detected
metadata['WellCounter'] = Counter(
metadata['Well_ArrayNames'])
except KeyError:
metadata['WellCounter'].append(Counter({'A1': 1}))
try:
# get the SceneCenter Position
sx = allscenes['CenterPosition'].split(',')[0]
sy = allscenes['CenterPosition'].split(',')[1]
metadata['SceneStageCenterX'].append(np.double(sx))
metadata['SceneStageCenterY'].append(np.double(sy))
except (TypeError, KeyError) as e:
print('Stage Positions XY not found :', e)
metadata['SceneStageCenterX'].append(0.0)
metadata['SceneStageCenterY'].append(0.0)
if metadata['SizeS'] > 1:
try:
well = allscenes[s]
metadata['Well_ArrayNames'].append(well['ArrayName'])
except KeyError as e:
try:
metadata['Well_ArrayNames'].append(well['Name'])
except KeyError as e:
# print('Well Name not found :', e)
try:
metadata['Well_ArrayNames'].append(well['@Name'])
except KeyError as e:
# print('Well @Name not found :', e)
print('Well Name not found. Using A1 instead')
metadata['Well_ArrayNames'].append('A1')
# get the well information
try:
metadata['Well_Indices'].append(well['Index'])
except KeyError as e:
try:
metadata['Well_Indices'].append(well['@Index'])
except KeyError as e:
print('Well Index not found :', e)
metadata['Well_Indices'].append(None)
try:
metadata['Well_PositionNames'].append(well['Name'])
except KeyError as e:
try:
metadata['Well_PositionNames'].append(well['@Name'])
except KeyError as e:
print('Well Position Names not found :', e)
metadata['Well_PositionNames'].append(None)
try:
metadata['Well_ColId'].append(
np.int(well['Shape']['ColumnIndex']))
except KeyError as e:
print('Well ColumnIDs not found :', e)
metadata['Well_ColId'].append(None)
try:
metadata['Well_RowId'].append(
np.int(well['Shape']['RowIndex']))
except KeyError as e:
print('Well RowIDs not found :', e)
metadata['Well_RowId'].append(None)
# count the content of the list, e.g. how many time a certain well was detected
metadata['WellCounter'] = Counter(metadata['Well_ArrayNames'])
# try:
if isinstance(allscenes, list):
try:
# get the SceneCenter Position
sx = allscenes[s]['CenterPosition'].split(',')[0]
sy = allscenes[s]['CenterPosition'].split(',')[1]
metadata['SceneStageCenterX'].append(np.double(sx))
metadata['SceneStageCenterY'].append(np.double(sy))
except KeyError as e:
print('Stage Positions XY not found :', e)
metadata['SceneCenterX'].append(0.0)
metadata['SceneCenterY'].append(0.0)
if not isinstance(allscenes, list):
metadata['SceneStageCenterX'].append(0.0)
metadata['SceneStageCenterY'].append(0.0)
# count the number of different wells
metadata['NumWells'] = len(metadata['WellCounter'].keys())
except (KeyError, TypeError) as e:
print('No valid Scene or Well information found:', e)
# get additional meta data about the experiment etc.
metadata_add = get_additional_metadata_czi(metadatadict_czi)
return metadata, metadata_add
def __init__(self, filename: str, dim2none: bool = False) -> None:
# get metadata dictionary using pylibCZIrw
with pyczi.open_czi(filename) as czidoc:
md_dict = czidoc.metadata
# get directory, filename, SW version and acquisition data
self.info = CziInfo(filename)
# get dimensions
self.pyczi_dims = czidoc.total_bounding_box
# get some additional metadata using aicspylibczi
try:
from aicspylibczi import CziFile
# get the general CZI object using aicspylibczi
aicsczi = CziFile(filename)
self.aics_dimstring = aicsczi.dims
self.aics_dims_shape = aicsczi.get_dims_shape()
self.aics_size = aicsczi.size
self.aics_ismosaic = aicsczi.is_mosaic()
self.aics_dim_order, self.aics_dim_index, self.aics_dim_valid = self.get_dimorder(
aicsczi.dims)
self.aics_posC = self.aics_dim_order["C"]
except ImportError as e:
print("Use Fallback values because:", e)
self.aics_dimstring = None
self.aics_dims_shape = None
self.aics_size = None
self.aics_ismosaic = None
self.aics_dim_order = None
self.aics_dim_index = None
self.aics_dim_valid = None
self.aics_posC = None
# get the pixel typed for all channels
self.pixeltypes = czidoc.pixel_types
self.isRGB = False
# determine pixel type for CZI array by reading XML metadata
self.pixeltype = md_dict["ImageDocument"]["Metadata"][
"Information"]["Image"]["PixelType"]
# check if CZI is a RGB file
if self.pixeltype in ["Bgr24", "Bgr48", "Bgr96Float"]:
self.isRGB = True
# determine pixel type for CZI array
self.npdtype, self.maxvalue = self.get_dtype_fromstring(
self.pixeltype)
# get the dimensions and order
self.image = CziDimensions(filename)
# try to guess if the CZI is a mosaic file
if self.image.SizeM is None or self.image.SizeM == 1:
self.ismosaic = False
else:
self.ismosaic = True
# get the bounding boxes
self.bbox = CziBoundingBox(filename)
# get information about channels
self.channelinfo = CziChannelInfo(filename)
# get scaling info
self.scale = CziScaling(filename, dim2none=dim2none)
# get objetive information
self.objective = CziObjectives(filename)
# get detector information
self.detector = CziDetector(filename)
# get detector information
self.microscope = CziMicroscope(filename)
# get information about sample carrier and wells etc.
self.sample = CziSampleInfo(filename)
# get additional metainformation
self.add_metadata = CziAddMetaData(filename)
#filename = r"D:\Testdata_Zeiss\CZI_Testfiles\CellDivision_T=10_Z=20_CH=1_DCV.czi"
#filename = r"D:\Testdata_Zeiss\CZI_Testfiles\S=1_HE_Slide_RGB_small.czi"
filename = r"D:\Testdata_Zeiss\CZI_Testfiles\FoLu_mCherryEB3_GFPMito_2_Airyscan Processing.czi"
######################################################################
# get the metadata as a dictionary
md, md_add = czt.get_metadata_czi(filename)
# read CZI using aicspylibczi
czi = CziFile(filename)
# for testing
# Get the shape of the data
print('czi_dims : ', czi.dims)
print('czi_dims_shape : ', czi.get_dims_shape())
print('czi_size : ', czi.size)
print('IsMoasic : ', czi.is_mosaic())
"""
if not czi.is_mosaic():
# get the shape for the 1st scene
scene = czt.CZIScene(czi, sceneindex=0)
shape_all = scene.shape_single_scene
# only update the shape for the scene if the CZI has an S-Dimension
if scene.hasS:
shape_all[scene.posS] = md['SizeS']
print('Shape all Scenes : ', shape_all)
print('DimString all Scenes : ', scene.single_scene_dimstr)
